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Objectives The aims of our study were to examine the anticholinergic drug use and to assess the association between anticholinergic burden and cognitive function in the multimorbid elderly patients of the MultiCare cohort.
Setting MultiCare was conducted as a longitudinal cohort study in primary care, located in eight different study centres in Germany.
Participants 3189 patients (59.3% female).
Primary and secondary outcome measures Baseline data were used for the following analyses. Drugs were classified according to the well-established anticholinergic drug scale (ADS) and the recently published German anticholinergic burden (German ACB). Cognitive function was measured using a letter digit substitution test (LDST) and a mixed-effect multivariate linear regression was performed to calculate the influence of anticholinergic burden on the cognitive function.
Results Patients used 1764 anticholinergic drugs according to ADS and 2750 anticholinergics according to the German ACB score (prevalence 38.4% and 53.7%, respectively). The mean ADS score was 0.8 (±1.3), and the mean German ACB score was 1.2 (±1.6) per patient. The most common ADS anticholinergic was furosemide (5.8%) and the most common ACB anticholinergic was metformin (13.7%). The majority of the identified anticholinergics were drugs with low anticholinergic potential: 80.2% (ADS) and 73.4% (ACB), respectively. An increasing ADS and German ACB score was associated with reduced cognitive function according to the LDST (−0.26; p=0.008 and −0.24; p=0.003, respectively).
Conclusion Multimorbid elderly patients are in a high risk for using anticholinergic drugs according to ADS and German ACB score. We especially need to gain greater awareness for the contribution of drugs with low anticholinergic potential from the cardiovascular system. As anticholinergic drug use is associated with reduced cognitive function in multimorbid elderly patients, the importance of rational prescribing and also deprescribing needs to be further evaluated.
Trial registration number ISRCTN89818205.
Highlights
• A big dataset reveals age-related alterations in EEG biomarkers and cognition.
• Prominent decline of individual alpha peak frequency primarily in temporal lobes.
• A positive association between individual alpha peak frequency and working memory.
• Absence of age-related alpha power decline when controlling for 1/f decay of the PSD.
• Alpha power is negatively associated with the speed of processing in elderly sample.
Abstract
While many structural and biochemical changes in the brain have previously been associated with older age, findings concerning functional properties of neuronal networks, as reflected in their electrophysiological signatures, remain rather controversial. These discrepancies might arise due to several reasons, including diverse factors determining general spectral slowing in the alpha frequency range as well as amplitude mixing between the rhythmic and non-rhythmic parameters. We used a large dataset (N = 1703, mean age 70) to comprehensively investigate age-related alterations in multiple EEG biomarkers taking into account rhythmic and non-rhythmic activity and their individual contributions to cognitive performance. While we found strong evidence for an individual alpha peak frequency (IAF) decline in older age, we did not observe a significant relationship between theta power and age while controlling for IAF. Not only did IAF decline with age, but it was also positively associated with interference resolution in a working memory task primarily in the right and left temporal lobes suggesting its functional role in information sampling. Critically, we did not detect a significant relationship between alpha power and age when controlling for the 1/f spectral slope, while the latter one showed age-related alterations. These findings thus suggest that the entanglement of IAF slowing and power in the theta frequency range, as well as 1/f slope and alpha power measures, might explain inconsistencies reported previously in the literature. Finally, despite the absence of age-related alterations, alpha power was negatively associated with the speed of processing in the right frontal lobe while 1/f slope showed no consistent relationship to cognitive performance. Our results thus demonstrate that multiple electrophysiological features, as well as their interplay, should be considered for the comprehensive assessment of association between age, neuronal activity, and cognitive performance.
Background: Multimorbidity is a common phenomenon in primary care. Until now, no clinical guidelines for multimorbidity exist. For the development of these guidelines, it is necessary to know whether or not patients are aware of their diseases and to what extent they agree with their doctor. The objectives of this paper are to analyze the agreement of self-reported and general practitioner-reported chronic conditions among multimorbid patients in primary care, and to discover which patient characteristics are associated with positive agreement.
Methods: The MultiCare Cohort Study is a multicenter, prospective, observational cohort study of 3,189 multimorbid patients, ages 65 to 85. Data was collected in personal interviews with patients and GPs. The prevalence proportions for 32 diagnosis groups, kappa coefficients and proportions of specific agreement were calculated in order to examine the agreement of patient self-reported and general practitioner-reported chronic conditions. Logistic regression models were calculated to analyze which patient characteristics can be associated with positive agreement.
Results: We identified four chronic conditions with good agreement (e.g. diabetes mellitus κ = 0.80;PA = 0,87), seven with moderate agreement (e.g. cerebral ischemia/chronic stroke κ = 0.55;PA = 0.60), seventeen with fair agreement (e.g. cardiac insufficiency κ = 0.24;PA = 0.36) and four with poor agreement (e.g. gynecological problems κ = 0.05;PA = 0.10).Factors associated with positive agreement concerning different chronic diseases were sex, age, education, income, disease count, depression, EQ VAS score and nursing care dependency. For example: Women had higher odds ratios for positive agreement with their GP regarding osteoporosis (OR = 7.16). The odds ratios for positive agreement increase with increasing multimorbidity in almost all of the observed chronic conditions (OR = 1.22-2.41).
Conclusions: For multimorbidity research, the knowledge of diseases with high disagreement levels between the patients' perceived illnesses and their physicians' reports is important. The analysis shows that different patient characteristics have an impact on the agreement. Findings from this study should be included in the development of clinical guidelines for multimorbidity aiming to optimize health care. Further research is needed to identify more reasons for disagreement and their consequences in health care.